There might questions which can arise in the mind of every R aspirant before they start to learn R Programming—Why Learn R Programming? So, what are the reasons to learn R Programming? We will answer this question here. Know the reasons why you must learn R Programming:
Unlike SAS or MATLAB, you can freely install, use, update, clone, modify, redistribute, and resell the R Programming. Hence, this saves companies money, but it also allows for easy upgrades, which is useful for a statistical programming language.
The R Programming can be run on Windows, Mac OS X, and Linux. Moreover, it can also import data from Microsoft Excel, Microsoft Access, MySQL, Oracle, and other programs.
The R Programming can easily handle large and complex data sets. R is also the best programming language to use for large, resource-intensive simulations, and it can be used on high-performance system clusters.
With approximately 2 million users, the R programming is one of the top programming languages of the decade.
In the current scenario, many new developments in statistics first appear as R packages.
The R Programming can easily integrate with document preparation systems. This means that statistical output and graphics from R can be embedded into word-processing documents.
The R programmers now have a global community of passionate users who regularly interacts on discussion forums and attend conferences. On the other hand, about hundreds of free libraries are available for your unlimited use, which covers the statistical areas of finance, cluster analysis, high-performance computing, and more.
Our R Programming online training course teaches learners how to use R Programming to explore data from a variety of sources by building inferential models and also generating graphs, charts, and other data representatives. In this course, you as a learner will be learning about the basics of R Programming and you will end with the confidence to start writing your R scripts. Here, you will not just be learning about the R fundamentals, you will be using R to solve problems related to data. We believe that using concrete examples makes the learning process easier and painless.
Moreover, you will also learn about the fundamentals of R syntax, which includes variables and doing simple operations with R’s most important data structures. Once you have covered learning the basics, you'll learn about reading and writing data in R. Finally, you will end with some important functions for character strings and dates in R Programming.
The audience for this online learning course are as follows:
The Prerequisites of this online course:
This online training course is typically designed with the beginner in mind. As learners may have experience in other computer programming languages, for this online course no prior programming language skills are required.
Q: What is R Programming is used for?
The R Programming is especially used for cleaning and then importing data in an open-source programming environment. On the other hand, R is frequently used by quantitative analysts that helps them to make key decisions from data. Moreover, it also gives a wide range of statistics that will be useful for Data Science, which includes statistical design and computing.
Q: Is R better than Python Language?
R and Python always serve different purposes in which the R Programming is mainly used for statistical analysis, whereas the Python programming language takes a broader approach to Data Science. If you have data that is already collected and cleaned and you just want to analyze it, then R is most useful. But in case you are scraping raw, messy data from some sources, Python may be more fitting.
Q: Are there any prerequisites to this course?
No! This is a beginner level online learning course for candidates just getting started with learning R Programming.
Q: Who should join this online learning course?
Undergraduates and also graduates looking to enter the domain of Data Analytics and wanting to become hands-on with R programming, then this online training course is for them.
Q: What will be my takeaway from this online course?
At the end of this online training course, the learner will be able to: